code: def __call__(self, caption):
      if self.task == "eval":
          if caption == "":
              caption = self.prompt
          else:
              caption = self.pre_caption(caption)
          return caption
      if caption == "" and self.task == "caption":
          caption = self.prompt + random.choice(
              TEMPLATES[self.modality][self.task]
          )
      elif self.task == "qa":
          caption = self.prompt + random.choice(
              TEMPLATES[self.modality][self.task]
          ).format(caption).replace("??", "?")
      elif self.task == "classification":
          if caption == "":
              caption = self.prompt + random.choice(
                  TEMPLATES[self.modality][self.task]
              )
          else:
              caption = self.classification_output(caption)
      else:
          caption = self.pre_caption(caption)
  
      return caption.lower().strip()
  
file_path: lavis/lavis/processors/instruction_text_processors.py
imports: import re
  from lavis.common.registry import registry
  from lavis.processors.base_processor import BaseProcessor
  from lavis.processors.randaugment import RandomAugment
  from omegaconf import OmegaConf
  from torchvision import transforms
  from torchvision.transforms.functional import InterpolationMode
  import random
  import nltk
  import pickle
label_desc: Use image node_id 4 for calling the BlipInstructionProcessor obj's underlying member method code with example usage: obj.__call__(caption) and returns: caption, caption